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It’s twenty-five years later from the time that I started working on this, and we understand something quite different about the Gospel of Thomas. What it looks like more than anything else, when you put it in context with other historical material, is Jewish mystical thought, or, Kabbalah. Kabbalah, we thought, was first known from written texts from the 10th to the 15th centuries from Spanish-Jewish communities. Before that, there was a prohibition on writing about secret teaching. It was mystical teaching that you were not supposed to write about because you don't know what fool could get ahold of it if you did. So, there was a prohibition on teaching anyone mystical Judaism before he was thirty-five, and certainly not to women. People were old by thirty-five, so you had to be a mature Jewish man to have access to that kind of teaching.

I, and others who study Jewish mystical thought at the Hebrew University in Jerusalem, suspect that this tradition goes back 2,000 years. This text says it’s Jesus’ secret teaching. Could it be? It could be. I don't know if it is or not, but it’s fascinating to see that what rabbis called “mystical thought” was labeled by Christian bishops in the 4th century to be heresy. That’s when I realized how religious imagination and politics coincide, because of the politics in the 4th century when Christian bishops were beginning to ask who this Jesus of Nazareth was. Jesus was God in human form, and he’s the only one who is the Son of God in human form. So, you can create a monopoly on divine energy and power with a religion that has the only access to the only person in the universe who ever channeled God directly, or was God and became human. That works very well for Orthodox Christianity. . . .

These discoveries are changing the way we understand how cultural traditions were shaped and how they became part of the culture in very different forms than they had begun. I find that enormously exciting. They involve everything from attitudes about gender and sexuality to attitudes about power and politics, about race, and gender, and ethnicity. That’s why I began to write about Adam and Eve. I mean, who cares about Adam and Eve? You realize that those traditions still play out in the culture—in the laws of the United States, or the laws of Britain, or the laws in Africa, the laws against homosexuality, and the ones that claim that the only true marriage can be a marriage between a man and a woman for the purpose of procreation. The Defense of Marriage Act was written by Professor Robert George at Princeton for G.W. Bush. These things still resonate, often very unconsciously, in the culture.

ELAINE PAGELS is the Harrington Spear Paine Professor of Religion at Princeton University. She is the author, most recently, of Why Religion?: A Personal Story.Elaine Pagels'Edge Bio Page

The general project that I’m working on is about the self and technology—what we understand by the self and how it’s changed over time. My sense is that the self is not a universal and purely abstract thing that you’re going to get at through a philosophy of principles. Here’s an example: Sigmund Freud considered his notion of psychic censorship (of painful or forbidden thoughts) to be one of his greatest contributions to his account of who we are. His thoughts about these ideas came early, using as a model the specific techniques that Czarist border guards used to censor the importation of potentially dangerous texts into Russia. Later, Freud began to think of the censoring system in Vienna during World War I—techniques applied to every letter, postcard, telegram and newspaper—as a way of getting at what the mind does. Another example: Cyberneticians came to a different notion of self, accessible from the outside, identified with feedback systems—an account of the self that emerged from Norbert Wiener’s engineering work on weapons systems during World War II. Now I see a new notion of the self emerging; we start by modeling artificial intelligence on a conception of who we are, and then begin seeing ourselves ever more in our encounter with AI.

PETER GALISON is the Joseph Pellegrino University Professor of the History of Science and of Physics at Harvard University and Director of the Collection of Historical Scientific Instruments. Peter Galison's Edge Bio Page

Corruption in general has a deleterious effect on the readiness of economic agents to invest. In the long run, it leads to a paralysis of economic life. But very often it is not that economic agents themselves have had the bad experience of being cheated and ruined, they just know that in this country, or in this part of the economy, or this building scene, there is a high likelihood that you will get cheated and that free riders can get away with it. Here again, reputation is absolutely essential, which is why transparency is so important. Trust can only be engendered by transparency. It's no coincidence that the name of the most influential non-governmental organization dealing with corruption is Transparency International.

KARL SIGMUND is professor of mathematics at the University of Vienna and one of the pioneers of evolutionary game theory. He is the author of Exact Thinking in Demented Times: The Vienna Circle and the Epic Quest for the Foundations of Science.Karl Sigmund's Edge Bio Page

Economic failures cause us serious problems. We need to build simulations of the economy at a much more fine-grained level that take advantage of all the data that computer technologies and the Internet provide us with. We need new technologies of economic prediction that take advantage of the tools we have in the 21st century.

Places like the US Federal Reserve Bank make predictions using a system that has been developed over the last eighty years or so. This line of effort goes back to the middle of the 20th century, when people realized that we needed to keep track of the economy. They began to gather data and set up a procedure for having firms fill out surveys, for having the census take data, for collecting a lot of data on economic activity and processing that data. This system is called “national accounting,” and it produces numbers like GDP, unemployment, and so on. The numbers arrive at a very slow timescale. Some of the numbers come out once a quarter, some of the numbers come out once a year. The numbers are typically lagged because it takes a lot of time to process the data, and the numbers are often revised as much as a year or two later. That system has been built to work in tandem with the models that have been built, which also process very aggregated, high-level summaries of what the economy is doing. The data is old fashioned and the models are old fashioned.

It's a 20th-century technology that's been refined in the 21st century. It's very useful, and it represents a high level of achievement, but it is now outdated. The Internet and computers have changed things. With the Internet, we can gather rich, detailed data about what the economy is doing at the level of individuals. We don't have to rely on surveys; we can just grab the data. Furthermore, with modern computer technology we could simulate what 300 million agents are doing, simulate the economy at the level of the individuals. We can simulate what every company is doing and what every bank is doing in the United States. The model we could build could be much, much better than what we have now. This is an achievable goal.

But we're not doing that, nothing close to that. We could achieve what I just said with a technological system that’s simpler than Google search. But we’re not doing that. We need to do it. We need to start creating a new technology for economic prediction that runs side-by-side with the old one, that makes its predictions in a very different way. This could give us a lot more guidance about where we're going and help keep the economic shit from hitting the fan as often as it does.

J. DOYNE FARMER is director of the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School, professor in the Mathematical Institute at the University of Oxford, and an external professor at the Santa Fe Institute. He was a co-founder of Prediction Company, a quantitative automated trading firm that was sold to the United Bank of Switzerland in 2006. J. Doyne Farmer's Edge Bio Page

The thing that stuck out was that self-control is simply a product of absolute brain size. It had more to do with your feeding ecology: How complex was your diet? How many things do you rely on to survive? That was a big surprise, because the idea that diet is shaping cognition has faded in many circles as the leading hypothesis for thinking about how psychology evolves. So, how do we move forward on testing ideas about the evolution of psychology? ... It's interesting to think about how this all came about. It all started in a bar.

BRIAN HARE is an associate professor of evolutionary anthropology at Duke University in North Carolina and founder the Duke Canine Cognition Center. He is the co-author (with Vanessa Woods) of The Genius of Dogs: How Dogs Are Smarter Than You Think. Brian Hare's Edge Bio Page

An even more recent and exciting revolution happening now is this connectomic revolution, where we’re able to map in exquisite detail the connections of a part of the brain, and soon even an entire insect brain. It’s giving us absolute answers to questions that we would have debated even just a few years ago; for example, does the insect brain work as an integrated system? And because we now have a draft of a connectome for the full insect brain, we can absolutely answer that question. That completely changes not just the questions that we’re asking, but our capacity to answer questions. There’s a whole new generation of questions that become accessible.

When I say a connectome, what I mean is an absolute map of the neural connections in a brain. That’s not a trivial problem. It's okay at one level to, for example with a light microscope, get a sense of the structure of neurons, to reconstruct some neurons and see where they go, but knowing which neurons connect with other neurons requires another level of detail. You need electron microscopy to look at the synapses.

ANDREW BARRON is the Australian Research Council Future Fellow and Deputy Head of the Department of Biological Sciences at Macquarie University. He is a neuroethologist with a particular focus on studying the neural mechanisms of honey bees. Andrew Barron's Edge Bio Page

The relationship between parents and children is the most important relationship. It gets more complicated in this case because, beyond the children being our natural children, we can influence them even beyond. We can influence them biologically, and we can use artificial intelligence as a new tool. I’m not a scientist or a technologist whatsoever, but the tools of artificial intelligence, in theory, are algorithm- or computer-based. In reality, I would argue that even an algorithm is biological because it comes from somewhere. It doesn’t come from itself. If it’s related to us as creators or as the ones who are, let’s say, enabling the algorithms, well, we’re the parents.

Who are those children that we are creating? What do we want them to be like as part of the earth, compared to us as a species and, frankly, compared to us as parents? They are our children. We are the parents. How will they treat us as parents? How do we treat our own parents? How do we treat our children? We have to think of these in the exact same way. Separating technology and humans the way we often think about these issues is almost wrong. If it comes from us, it’s the same thing. We have a responsibility. We have the power and the imagination to shape this future generation. It’s exciting, but let’s just make sure that they view us as their parents. If they view us as their parents, we will have a connection.

Investor and philanthropist NICOLAS BERGGRUEN is the chairman of the Berggruen Institute, and founder of the 21st Century Council, the Council for the Future of Europe, and the Think Long Committee for California.Nicolas Berggruen's Edge Bio Page

We don’t know enough about important issues that impact women. We don’t know enough about potential side effects of using hormonal contraception. There’s a lot of speculation about it, but most of that speculation is problematic. If you eliminate women’s hormone cycles, what are the implications? That’s an important question. We still don’t know enough about hormone supplements for women later in life. We don’t even know enough about fertility. The data are also problematic. The data on fertility in women’s third, fourth, fifth decades of life are based on ancient records, 200 years old. The statistics that doctors will cite when they are telling women whether they need to see a fertility specialist or not are from a period before modern medicine was really in place, which is outrageous. More recognition of the biological influences on women’s behavior is going to awaken these areas of research, and that will have a positive impact.

​MARTIE HASELTON is a professor of psychology and communication studies at the Institute for Society and Genetics and UCLA. She is the author of Hormonal: The Hidden Intelligence of Hormones—How They Drive Desire, Shape Relationships, Influence Our Choices, and Make Us Wiser. Martie Haselton's Edge Bio

Aaron Sloman, the British philosopher, has this great phrase: the space of possible minds. The idea is that the space of possible minds encompasses not only the biological minds that have arisen on this earth, but also extraterrestrial intelligence, and whatever forms of biological or evolved intelligence are possible but have never occurred, and artificial intelligence in the whole range of possible ways we might build AI.

I love this idea of the space of possible minds, trying to understand the structure of the space of possible minds in some kind of principled way. How is consciousness distributed through this space of possible minds? Is something that has a sufficiently high level of intelligence necessarily conscious? Is consciousness a prerequisite for human-level intelligence or general intelligence? I tend to think the answer to that is no, but it needs to be fleshed out a little bit. We need to break down the concept of consciousness into different aspects, all of which tend to occur together in humans, but can occur independently, or some subset of these can occur on its own in an artificial intelligence. Maybe we can build an AI that clearly has an awareness and understanding of the world. We very much want to say, "It's conscious of its surroundings, but it doesn't experience any emotion and is not capable of suffering." We can imagine building something that has some aspects of consciousness and lacks others.

MURRAY SHANAHAN is a professor of cognitive robotics at Imperial College London and a senior research scientist at DeepMind. Murray Shanahan's Edge Bio Page

We should be very careful in thinking about whether we’re working on the right problems. If we don’t, that ties into the problem that we don’t have experimental evidence that could move us forward. We're trying to develop theories that we use to find out which are good experiments to make, and these are the experiments that we build.

We build particle detectors and try to find dark matter; we build larger colliders in the hope of producing new particles; we shoot satellites into orbit and try to look back into the early universe, and we do that because we hope there’s something new to find there. We think there is because we have some idea from the theories that we’ve been working on that this would be something good to probe.

If we are working with the wrong theories, we are making the wrong extrapolations, we have the wrong expectations, we make the wrong experiments, and then we don’t get any new data. We have no guidance to develop these theories. So, it’s a chicken and egg problem. We have to break the cycle. I don’t have a miracle cure to these problems. These are hard problems. It’s not clear what a good theory is to develop. I’m not any wiser than all the other 20,000 people in the field.